Gabor filters for rotation invariant texture classification

A Gabor filter based feature extraction scheme for texture classification is proposed. By using a novel set of circularly symmetric filters, rotation invariance is achieved. The scheme offers a high classification performance on textures at any orientation using both fewer features and a smaller area of analysis than most existing schemes. The performance of the scheme on noisy images is also investigated, demonstrating a high robustness to noise.

[1]  W. K. Lam,et al.  Classification of rotated and scaled textures by local linear operators , 1995, Proceedings of ISCAS'95 - International Symposium on Circuits and Systems.

[2]  C.-C. Jay Kuo,et al.  Texture analysis and classification with tree-structured wavelet transform , 1993, IEEE Trans. Image Process..

[3]  Cedric Nishan Canagarajah,et al.  Robust rotation invariant texture classification , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[4]  Mark S. Nixon,et al.  Statistical geometrical features for texture classification , 1995, Pattern Recognit..

[5]  Cedric Nishan Canagarajah,et al.  A robust automatic clustering scheme for image segmentation using wavelets , 1996, IEEE Trans. Image Process..

[6]  Rama Chellappa,et al.  Separability based tree structured local basis selection for texture classification , 1994, Proceedings of 1st International Conference on Image Processing.

[7]  R. Porter,et al.  Robust rotation-invariant texture classification: wavelet, Gabor filter and GMRF based schemes , 1997 .

[8]  Wilson S. Geisler,et al.  Multichannel Texture Analysis Using Localized Spatial Filters , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Rama Chellappa,et al.  Classification of textures using Gaussian Markov random fields , 1985, IEEE Trans. Acoust. Speech Signal Process..

[10]  Cedric Nishan Canagarajah,et al.  Rotation invariant texture classification schemes using GMRFs and wavelets , 1996 .